{"id":"https://openalex.org/W2116266897","doi":"https://doi.org/10.1109/tac.2010.2090707","title":"Robust Filtering Through Coherent Lower Previsions","display_name":"Robust Filtering Through Coherent Lower Previsions","publication_year":2010,"publication_date":"2010-11-10","ids":{"openalex":"https://openalex.org/W2116266897","doi":"https://doi.org/10.1109/tac.2010.2090707","mag":"2116266897"},"language":"en","primary_location":{"id":"doi:10.1109/tac.2010.2090707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tac.2010.2090707","pdf_url":null,"source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automatic Control","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10651/9834","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044312043","display_name":"Alessio Benavoli","orcid":"https://orcid.org/0000-0002-2522-7178"},"institutions":[{"id":"https://openalex.org/I2614128279","display_name":"Dalle Molle Institute for Artificial Intelligence Research","ror":"https://ror.org/013355g38","country_code":"CH","type":"facility","lineage":["https://openalex.org/I15196421","https://openalex.org/I2614128279","https://openalex.org/I57201433"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Alessio Benavoli","raw_affiliation_strings":["Istituto Dalle Molle di Studi sull Intelligenza Artificiale, Lugano, Switzerland","Ist. Dalle Molle di Studi sull'Intell. Artificiale (IDSIA), Lugano, Switzerland"],"affiliations":[{"raw_affiliation_string":"Istituto Dalle Molle di Studi sull Intelligenza Artificiale, Lugano, Switzerland","institution_ids":["https://openalex.org/I2614128279"]},{"raw_affiliation_string":"Ist. Dalle Molle di Studi sull'Intell. Artificiale (IDSIA), Lugano, Switzerland","institution_ids":["https://openalex.org/I2614128279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007403791","display_name":"Marco Zaffalon","orcid":"https://orcid.org/0000-0001-8908-1502"},"institutions":[{"id":"https://openalex.org/I2614128279","display_name":"Dalle Molle Institute for Artificial Intelligence Research","ror":"https://ror.org/013355g38","country_code":"CH","type":"facility","lineage":["https://openalex.org/I15196421","https://openalex.org/I2614128279","https://openalex.org/I57201433"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Marco Zaffalon","raw_affiliation_strings":["Istituto Dalle Molle di Studi sull Intelligenza Artificiale, Lugano, Switzerland","Ist. Dalle Molle di Studi sull'Intell. Artificiale (IDSIA), Lugano, Switzerland"],"affiliations":[{"raw_affiliation_string":"Istituto Dalle Molle di Studi sull Intelligenza Artificiale, Lugano, Switzerland","institution_ids":["https://openalex.org/I2614128279"]},{"raw_affiliation_string":"Ist. Dalle Molle di Studi sull'Intell. Artificiale (IDSIA), Lugano, Switzerland","institution_ids":["https://openalex.org/I2614128279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025386662","display_name":"Enrique Miranda","orcid":"https://orcid.org/0000-0001-7763-3779"},"institutions":[{"id":"https://openalex.org/I165339363","display_name":"Universidad de Oviedo","ror":"https://ror.org/006gksa02","country_code":"ES","type":"education","lineage":["https://openalex.org/I165339363"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Enrique Miranda","raw_affiliation_strings":["Universidad de Oviedo, Oviedo, Spain","Dipt. de Estadistica e l.O. y D.M, Univ. de Oviedo, Oviedo, Spain"],"affiliations":[{"raw_affiliation_string":"Universidad de Oviedo, Oviedo, Spain","institution_ids":["https://openalex.org/I165339363"]},{"raw_affiliation_string":"Dipt. de Estadistica e l.O. y D.M, Univ. de Oviedo, Oviedo, Spain","institution_ids":["https://openalex.org/I165339363"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5044312043"],"corresponding_institution_ids":["https://openalex.org/I2614128279"],"apc_list":null,"apc_paid":null,"fwci":6.9675,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.96808177,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"56","issue":"7","first_page":"1567","last_page":"1581"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12135","display_name":"Fuzzy Systems and Optimization","score":0.9868999719619751,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.6870619058609009},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.640363335609436},{"id":"https://openalex.org/keywords/filtering-problem","display_name":"Filtering problem","score":0.5868176817893982},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5739811062812805},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5541012287139893},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.5166716575622559},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.5144665241241455},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5059666037559509},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.48087647557258606},{"id":"https://openalex.org/keywords/convex-set","display_name":"Convex set","score":0.47393232583999634},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.45523858070373535},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4459128677845001},{"id":"https://openalex.org/keywords/convex-combination","display_name":"Convex combination","score":0.42306065559387207},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4173222780227661},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36392414569854736},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.34116870164871216},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.3135189116001129},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2513889968395233},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1624908447265625},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.14005330204963684}],"concepts":[{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.6870619058609009},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.640363335609436},{"id":"https://openalex.org/C41614226","wikidata":"https://www.wikidata.org/wiki/Q5449244","display_name":"Filtering problem","level":4,"score":0.5868176817893982},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5739811062812805},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5541012287139893},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.5166716575622559},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.5144665241241455},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5059666037559509},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.48087647557258606},{"id":"https://openalex.org/C49870271","wikidata":"https://www.wikidata.org/wiki/Q193657","display_name":"Convex set","level":4,"score":0.47393232583999634},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.45523858070373535},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4459128677845001},{"id":"https://openalex.org/C111110010","wikidata":"https://www.wikidata.org/wiki/Q2627315","display_name":"Convex combination","level":4,"score":0.42306065559387207},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4173222780227661},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36392414569854736},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.34116870164871216},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.3135189116001129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2513889968395233},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1624908447265625},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.14005330204963684},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tac.2010.2090707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tac.2010.2090707","pdf_url":null,"source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automatic Control","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.228.8349","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.228.8349","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.idsia.ch/%7Ezaffalon/papers/2011tac-filtering.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.299.4593","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.299.4593","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.idsia.ch/idsiareport/IDSIA-05-09.pdf","raw_type":"text"},{"id":"pmh:oai:digibuo.uniovi.es:10651/9834","is_oa":true,"landing_page_url":"http://hdl.handle.net/10651/9834","pdf_url":null,"source":{"id":"https://openalex.org/S4306402334","display_name":"Consultation of the Doctoral Thesis Database (TESEO) (Ministerio de Educaci\u00f3n, Cultura y Deporte)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2801976130","host_organization_name":"Ministerio de Educaci\u00f3n Cultura y Deporte","host_organization_lineage":["https://openalex.org/I2801976130"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WOK","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:digibuo.uniovi.es:10651/9834","is_oa":true,"landing_page_url":"http://hdl.handle.net/10651/9834","pdf_url":null,"source":{"id":"https://openalex.org/S4306402334","display_name":"Consultation of the Doctoral Thesis Database (TESEO) (Ministerio de Educaci\u00f3n, Cultura y Deporte)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2801976130","host_organization_name":"Ministerio de Educaci\u00f3n Cultura y Deporte","host_organization_lineage":["https://openalex.org/I2801976130"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WOK","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5377570677","display_name":null,"funder_award_id":"10030","funder_id":"https://openalex.org/F4320321942","funder_display_name":"Hasler Stiftung"},{"id":"https://openalex.org/G5599649393","display_name":null,"funder_award_id":"200020","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321942","display_name":"Hasler Stiftung","ror":"https://ror.org/04m3t9183"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W127194676","https://openalex.org/W1488706289","https://openalex.org/W1494614627","https://openalex.org/W1844548710","https://openalex.org/W1968293352","https://openalex.org/W1969344405","https://openalex.org/W1969759674","https://openalex.org/W1988520084","https://openalex.org/W1997265316","https://openalex.org/W2004783587","https://openalex.org/W2008118542","https://openalex.org/W2025934416","https://openalex.org/W2033810643","https://openalex.org/W2067340154","https://openalex.org/W2073037151","https://openalex.org/W2077611006","https://openalex.org/W2094492456","https://openalex.org/W2097701432","https://openalex.org/W2101413186","https://openalex.org/W2101975205","https://openalex.org/W2117397690","https://openalex.org/W2126163471","https://openalex.org/W2135765818","https://openalex.org/W2137229244","https://openalex.org/W2155234026","https://openalex.org/W2158518844","https://openalex.org/W2160209952","https://openalex.org/W2160337655","https://openalex.org/W2165752801","https://openalex.org/W2170768685","https://openalex.org/W2171277949","https://openalex.org/W2172654550","https://openalex.org/W2797148637","https://openalex.org/W2974222084","https://openalex.org/W3102934921","https://openalex.org/W4210427261","https://openalex.org/W4242951679","https://openalex.org/W4301347335","https://openalex.org/W6629024266","https://openalex.org/W6629616394","https://openalex.org/W6680302712","https://openalex.org/W6682966296"],"related_works":["https://openalex.org/W2391247224","https://openalex.org/W2363904277","https://openalex.org/W868123585","https://openalex.org/W2300145982","https://openalex.org/W2376997122","https://openalex.org/W2365830408","https://openalex.org/W4296997005","https://openalex.org/W2580512045","https://openalex.org/W2734394069","https://openalex.org/W2040676043"],"abstract_inverted_index":{"The":[0,101,114,133],"classical":[1],"filtering":[2],"problem":[3,39],"is":[4,20,45,72,104,135,142,179],"re-examined":[5],"to":[6,60,106,128,130,182,195],"take":[7],"into":[8],"account":[9],"imprecision":[10],"in":[11,22,63,80,188,205],"the":[12,15,36,64,77,89,93,97,136,161,167,171,183,189,202],"knowledge":[13],"about":[14],"probabilistic":[16],"relationships":[17],"involved.":[18],"Imprecision":[19],"modeled":[21],"this":[23],"paper":[24],"by":[25,75],"closed":[26,53],"convex":[27,54,147],"sets":[28],"of":[29,35,56,82,88,92,99,110,117,120,146,149,185],"probabilities.":[30],"We":[31],"derive":[32],"a":[33,42,118,143,150,155,197,207],"solution":[34,103,178],"state":[37,68],"estimation":[38],"under":[40],"such":[41,206],"framework":[43],"that":[44,86,176],"very":[46],"general:":[47],"it":[48],"can":[49],"deal":[50],"with":[51,157,170],"any":[52],"set":[55,98],"probability":[57],"distributions":[58,122],"used":[59],"characterize":[61],"uncertainty":[62],"prior,":[65],"likelihood,":[66],"and":[67,191],"transition":[69],"models.":[70],"This":[71,174],"made":[73,145],"possible":[74],"formulating":[76],"theory":[78],"directly":[79],"terms":[81],"coherent":[83,111],"lower":[84,90,112],"previsions,":[85],"is,":[87],"envelopes":[91],"expectations":[94],"obtained":[95],"from":[96],"distributions.":[100,159],"general":[102],"specialized":[105],"two":[107],"particular":[108],"classes":[109],"previsions.":[113],"first":[115],"consists":[116],"family":[119,144],"Gaussian":[121],"whose":[123],"means":[124],"are":[125],"only":[126],"known":[127,151],"belong":[129],"an":[131],"interval.":[132],"second":[134],"so-called":[137],"linear-vacuous":[138],"mixture":[139],"model,":[140],"which":[141],"combinations":[148],"nominal":[152],"distribution":[153],"(e.g.,":[154],"Gaussian)":[156],"arbitrary":[158],"For":[160],"latter":[162],"case,":[163],"we":[164],"empirically":[165],"compare":[166],"proposed":[168],"estimator":[169],"Kalman":[172,203],"filter.":[173],"shows":[175],"our":[177],"more":[180,198],"robust":[181],"presence":[184],"modelling":[186],"errors":[187],"system":[190],"that,":[192],"hence,":[193],"appears":[194],"be":[196],"realistic":[199],"approach":[200],"than":[201],"filter":[204],"case.":[208]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":5}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
